openmv'如何用多模板识别，来识别两位或三位数字
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import time, sensor, image from image import SEARCH_EX, SEARCH_DS #从imgae模块引入SEARCH_EX和SEARCH_DS。使用from import仅仅引入SEARCH_EX, #SEARCH_DS两个需要的部分，而不把image模块全部引入。 # Reset sensor sensor.reset() # Set sensor settings sensor.set_contrast(1) sensor.set_gainceiling(16) # Max resolution for template matching with SEARCH_EX is QQVGA sensor.set_framesize(sensor.QQVGA) # You can set windowing to reduce the search image. #sensor.set_windowing(((640-80)//2, (480-60)//2, 80, 60)) sensor.set_pixformat(sensor.GRAYSCALE) # Load template. # Template should be a small (eg. 32x32 pixels) grayscale image. templates = ["/0.pgm","/1.pgm", "/2.pgm", "/3.pgm"] #保存多个模板 numerical = [0,1,2,3] coordinate_x =[0,0,0,0] numerical_x = [0,0,0,0] i=0 #加载模板图片 clock = time.clock() # Run template matching while (True): clock.tick() img = sensor.snapshot() # find_template(template, threshold, [roi, step, search]) # ROI: The region of interest tuple (x, y, w, h). # Step: The loop step used (y+=step, x+=step) use a bigger step to make it faster. # Search is either image.SEARCH_EX for exhaustive search or image.SEARCH_DS for diamond search # # Note1: ROI has to be smaller than the image and bigger than the template. # Note2: In diamond search, step and ROI are both ignored. for t in templates: template = image.Image(t) #对每个模板遍历进行模板匹配 r = img.find_template(template, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60)) #find_template(template, threshold, [roi, step, search]),threshold中 #的0.7是相似度阈值,roi是进行匹配的区域（左上顶点为（10，0），长80宽60的矩形）， #注意roi的大小要比模板图片大，比frambuffer小。 #把匹配到的图像标记出来 if r: img.draw_rectangle(r) #print(templates.index(t)) coordinate_x [i] = r[0] numerical_x [i] = numerical[templates.index(t)] i+=1 print( numerical_x) #打印模板名字 print( coordinate_x) if i==3: i=0想不到方法了，我只想保存0到9模板然后识别两位数字或多位，求大神给点思路
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你的图像中的数字，是固定位置的吗？
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同问，我的是同一个位置，有好的程序么？谢谢
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请问你的问题解决了么？怎么解决的？